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While prior research has examined auditors’ responses to corruption-related risks in the context of foreign corruption violations and political cronyism or corruption, these studies are limited to economies or regions with weak political environments or clients with an observable act of noncompliance with a law or regulation. We extend the understanding of auditor response to client corruption with a Google document-frequency based measure that captures both the actual and perceived prevalence of illegal acts by firms. A key advantage of our client-specific measure is that it provides a holistic proxy of corruption by capitalizing on widely disseminated textual information in decentralized internet databases. We show that our Google-based corruption measure is a leading predictor of client violations of the Foreign Corrupt Practices Act (FCPA) and provides incremental predictive power beyond regional corruption proxies. Importantly, we predict and find that auditors’ input and output behavior is associated with this novel corruption measure. Specifically, in response to client corruption, auditors change their production inputs and charge higher audit fees. Related to audit output, we find that client corruption is positively associated with financial statement restatements and that auditor decision errors (client and auditor reporting) are more prevalent for corrupt clients. Overall, these findings show that while auditors appropriately price for corruption risk, their execution of the audit does not fully adjust for the risk identified.
Kecia Williams Smith, North Carolina A&T State University
Jennifer R Joe, University of Delaware
Nerissa C Brown, University of Illinois at Urbana-Champaign
Joseph Han Stice, Chinese University of Hong Kong